Effect of Temperature on Moisture Sorption Isotherms and Monolayer Moisture Content of Bermuda Grass (Cynodon Dactylon)

M. AL-MAHASNEH1, F. ALKOAIK1, A. KHALIL1, R. FULLEROS1 and A. EL-WAZIRY2
1 Department of Agricultural Engineering, College of Food and Agricultural Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia
2 Departmet of Animal Production, College of Food and Agricultural Sciences, King Saud University, Riyadh, Kingdom of Saudi Arabia

Abstract

AL-MAHASNEH, M., F. ALKOAIK, A. KHALIL, R. FULLEROS and A. EL-WAZIRY, 2014. Effect of temperature on moisture sorption isotherms and monolayer moisture content of bermuda grass (Cynodon dactylon). Bulg. J. Agric. Sci., 20: 1289-1294

 

Bermuda grass is widely grown in Saudi Arabia as a turf grass. It is highly tolerant to drought and hot weather. It can be compressed to form pellets, which can be used as livestock, or energy pellets similar to charcoals. Drying is required to process the grass into a safe storage condition. Moisture sorption isotherms are required to design and optimize the drying process of the grass. Therefore, moisture sorption isotherms were studied using gravimetric methods at temperatures ranging from 20 to 40°C. Both conventional analytical moisture sorption isotherms (MSI) and artificial neural networks (ANNs) were used to model the relationship between equilibrium moisture content (EMC) and equilibrium relative humidity (ERH). The results showed that Modified Halsey equation was the best representative of MSIs. However, ANNs were also found to outperform MSI analytical models with R2 = 0.991 and a root mean square error (RMSE ) = 1.17. Monolayer moisture content was also found to decrease linearly with EMC from 0.074 to 0.047 (decimal w.b.) over the temperature range investigated.

Key words: equilibrium relative humidity; drying; Bermuda grass; artificial neural networks

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